1. Field
The present invention relates generally to computer vision and, more specifically, to three dimensional (3D) scene analysis for automatically visually tracking multiple bodies in motion via multiple cameras.
2. Description
A closed world is described by a finite set of objects and by a internal state for each of the instantiated objects. When one captures video in a closed world, each pixel of every frame should be explained as belonging to one (or a combination) of the known objects in the world. In one example, of a soccer match, the closed world contains players, referees, field lines, goals, the ball, and grass. The internal state of the closed world over time (e.g., the positions of the players) however, is unknown and may be computed from the incoming visual data in a sequence of video frames. Robust visual processing routines for computing the internal state may be selected using prior knowledge about the domain and any information that has already been learned about the state of the world. Closed worlds allow us to add constraints to the problem of tracking objects and therefore increase the robustness and reduce the complexity of the tracking problem.
Video annotation is the task of generating descriptions of video sequences that can be used for indexing, retrieval, and summarization. Video annotation is different from general image understanding in that one is primarily interested in the detection of specific events, as opposed to understanding the unbound semantics of the scene. Many video annotation domains require documenting interactions between people and other non-rigid objects against non-static backgrounds and in unconstrained motion.
Methods to track moving objects in video sequences for purposes of video annotation are being developed. Some work is underway in developing tracking systems for closed worlds such as for professional sports events. In one known system, analysis of the movement of players in a soccer match is implemented by examining color histograms of player's uniforms. However, the results of such a system may be negatively affected by changing levels of illumination in a video sequence. Hence, novel methods of tracking moving objects in an image sequence for video annotation or other purposes are desired.